Commit 11cf5a0c authored by Maria Kleppestø Mcculloch's avatar Maria Kleppestø Mcculloch
Browse files

Some changes

parent 804f5220
......@@ -49,7 +49,7 @@ One can use the code present in main.py to compute the baseline. In order to com
### 2. Compute quality metrics
This can be run as long as there are some baselines (.npy file) in data/ . One does not need to have run ``computeBaselines()`` in the same run. In order to compute metrics, one needs to init a ``QualityEvaluator`` object, and run ``Detection_Arcface_init`` in order to init ArcFace. Then, one needs to call ``ComputeMetric("name", subjectnr, samplenr)``. If the metric is suported, it will be computed. Then, one needs to call the ``SaveMetric()`` if one wants the metric to be read to file. This cane be done using main by doing the following:
This can be run as long as there are some baselines (.npy file) in data/ . One does not need to have run ``computeBaselines()`` in the same run. In order to compute metrics, one needs to init a ``QualityEvaluator`` object, and run ``Detection_Arcface_init()`` in order to init ArcFace. Then, one needs to call ``ComputeMetric("name", subjectnr, samplenr)``. If the metric is suported, it will be computed. Then, one needs to call the ``SaveMetric()`` if one wants the metric to be read to file. This cane be done using main by doing the following:
#### i. Uncomment the following lines in main.py:
......@@ -79,7 +79,7 @@ This can be run as long as there are some baselines (.npy file) in data/ . One d
### 3. Plot quality metrics
This can be run as long as there are some baselines (.npy file in data/), and some quality scores for the specified metric (.npy file in data/ or .csv file in data/brisque/ ). In order to plot metrics, one needs to init a ``QualityEvaluator`` object. Then, one needs to call ``PlotMetric("Method", "Metric", subnr=[subnr], samnr=[sampnr])``. If the metric is suported, it will be plotted. In order to do this in main, do the following:
This can be run as long as there are some baselines (.npy file in data/), and some quality scores for the specified metric (.npy file in data/ or .csv file in data/brisque/ ). In order to plot metrics, one needs to init a ``QualityEvaluator`` object and run ``Detection_Arcface_init()`` . Then, one needs to call ``PlotMetric("Method", "Metric", subnr=[subnr], samnr=[sampnr])``. If the metric is suported, it will be plotted. In order to do this in main, do the following:
#### i. Uncomment the following lines in main.py:
......
......@@ -27,12 +27,11 @@ imgsdir = 'img/CasiaV2/CasiaSelection/'
## STEP 1: COMPUTE BASELINES ##
###############################
# Init Evaulator
print("--* Initing Evaulator")
# "subjectnr/samplenr" = 000001/001.jpg
#QualEval = QualityEvaluator("ArcFaceCasiaV2", projectpath, imgsdir, "subjectnr/samplenr")
QualEval = QualityEvaluator("ArcFaceCasiaV2", projectpath, imgsdir, "subjectnr/samplenr")
print("-- * Initing Arcface")
#QualEval.ArcFace_init()
......@@ -55,42 +54,41 @@ print("--* Saving Baselines")
## STEP 2: COMPUTE METRICS ##
######################################
## NB! REMEMBER TO UNCOMMOENT the QualEval initiation ON LINE 35
## NB! REMEMBER TO UNCOMMENT the QualEval initiation ON LINE 35
'''
# Compute metrics
print("--* Detecting Init")
QualEval.Detection_Arcface_init()
#QualEval.Detection_Arcface_init()
print("--* Computing metrics")
QualEval.ComputeMetric("sharpness", params[0], params[1])
QualEval.ComputeMetric("focus", params[0], params[1])
#QualEval.ComputeMetric("sharpness", params[0], params[1])
#QualEval.ComputeMetric("focus", params[0], params[1])
print("--* Save metric")
QualEval.SaveMetric("sharpness")
QualEval.SaveMetric("focus")
#QualEval.SaveMetric("sharpness")
#QualEval.SaveMetric("focus")
'''
##########################
## STEP 3: PLOT METRICS ##
##########################
## NB! REMEMBER TO UNCOMMOENT the QualEval initiation ON LINE 35 AND QualEval.Detection_Arcface_init() ON LINE 63
## NB! REMEMBER TO UNCOMMOENT the QualEval initiation ON LINE 35 and QualEval.Detection_Arcface_init() ON LINE 63
'''
print("--* Plotting Metrics")
QualEval.PlotMetric("EDC", "focus",subnr=params[0], sampnr=params[1])
QualEval.PlotMetric("EDC", "sharpness",subnr=params[0], sampnr=params[1])
QualEval.PlotMetric("EDC", "brisque",subnr=params[0], sampnr=params[1], metric_name="data/brisque/quality_values_aug")
#QualEval.PlotMetric("EDC", "focus",subnr=params[0], sampnr=params[1])
#QualEval.PlotMetric("EDC", "sharpness",subnr=params[0], sampnr=params[1])
#QualEval.PlotMetric("EDC", "brisque",subnr=params[0], sampnr=params[1], metric_name="data/brisque/quality_values_aug")
print("DET; Focus")
QualEval.PlotMetric("DET", "focus",subnr=params[0], sampnr=params[1])
#QualEval.PlotMetric("DET", "focus",subnr=params[0], sampnr=params[1])
print("DET; Sharpness")
QualEval.PlotMetric("DET", "sharpness",subnr=params[0], sampnr=params[1])
#QualEval.PlotMetric("DET", "sharpness",subnr=params[0], sampnr=params[1])
print("DET; Brisque")
QualEval.PlotMetric("DET", "brisque",subnr=params[0], sampnr=params[1], metric_name="data/brisque/quality_values_aug")
#QualEval.PlotMetric("DET", "brisque",subnr=params[0], sampnr=params[1], metric_name="data/brisque/quality_values_aug")
#QualEval.PlotDETCurve(params[0],params[1])
QualEval.PlotDETCurve(params[0],params[1])
'''
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